Conditional Iterative Proportional Fitting for Gaussian Distributions

✍ Scribed by Erhard Cramer

• Publisher: Elsevier Science
• Year: 1998
• Tongue: English
• Weight: 345 KB
• Volume: 65
• Category: Article
• ISSN: 0047-259X
• DOI: 10.1006/jmva.1998.1739

✦ Synopsis

A Gaussian version of the iterative proportional fitting procedure (IFP-P) was applied by Speed and Kiiveri to solve the likelihood equations in graphical Gaussian models. The calculation of the maximum likelihood estimates can be seen as the problem to find a Gaussian distribution with prescribed Gaussian marginals. We extend the Gaussian version of the IPF-P so that additionally given conditionals of Gaussian type are taken into account. The convergence of both proposed procedures, called conditional iterative proportional fitting procedures (CIPF-P), is proved.